Scholarlink

<p>As a multi-functional public service facility capable of converting travel costs into tourism benefits, Tourist Scenic Byways play a critical role in creating value by connecting tourist destinations or attractions. This paper constructs a multi-scale nested evaluation model for Tourist Scenic Byways, integrating 21 factors across three dimensions: visual characteristics, Scene Characteristics, and Attractor Characteristics. Dijkstra algorithm is applied to simulate the route selection of Tourist Scenic Byways across three spatial scales—Guangxi Zhuang Autonomous Region, Guilin City, and Yangshuo County—and to optimize the network based on the current road system. The results of the study indicate: (1) A total of 342 Tourist Scenic Byways were identified, including 53 Provincial Tourist Scenic Byways, 77 Municipal Tourist Scenic Byways and 212 County Tourist Scenic Byways. (2) Provincial Tourist Scenic Byways can connect 92 important tourist attractions in the provincial area, with a connection rate of 29.21%; Municipal Tourist Scenic Byways can connect 26 important tourist attractions in the municipal area, with a connection rate of 56.52%; and County Tourist Scenic Byways have a connection rate of 100.00%, connecting all the important tourist attractions in the county area.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Linking Beautiful Scenes with Path Algorithms: A Study on Route Selection of Multi-Scale Tourist Scenic Byways

  • 期刊论文

  • 发表日期：

    2026年1月7日

查看全文
  • kangdi Li,
  • Changle Yu,
  • Maojie Zhou,
  • Yaming Fan

摘要

As a multi-functional public service facility capable of converting travel costs into tourism benefits, Tourist Scenic Byways play a critical role in creating value by connecting tourist destinations or attractions. This paper constructs a multi-scale nested evaluation model for Tourist Scenic Byways, integrating 21 factors across three dimensions: visual characteristics, Scene Characteristics, and Attractor Characteristics. Dijkstra algorithm is applied to simulate the route selection of Tourist Scenic Byways across three spatial scales—Guangxi Zhuang Autonomous Region, Guilin City, and Yangshuo County—and to optimize the network based on the current road system. The results of the study indicate: (1) A total of 342 Tourist Scenic Byways were identified, including 53 Provincial Tourist Scenic Byways, 77 Municipal Tourist Scenic Byways and 212 County Tourist Scenic Byways. (2) Provincial Tourist Scenic Byways can connect 92 important tourist attractions in the provincial area, with a connection rate of 29.21%; Municipal Tourist Scenic Byways can connect 26 important tourist attractions in the municipal area, with a connection rate of 56.52%; and County Tourist Scenic Byways have a connection rate of 100.00%, connecting all the important tourist attractions in the county area.